Optimization designs refer to experimental design strategies that are specifically structured to optimize a process, product, or system. The goal of these designs is to identify the combination of factors (inputs) that lead to the best possible outcome (response) according to a defined objective, such as maximizing performance, minimizing cost, or finding the most efficient operating conditions.
Optimization designs are particularly useful in fields like manufacturing, engineering, product development, and process improvement, where the goal is often to find the “optimal” settings of several variables that maximize or minimize a particular response variable (e.g., efficiency, yield, cost, etc.).
Once a screening design is used and influential factors are identified, the next goal usually consists of optimising their settings.
This module covers the construction of experimental designs for optimisation applications. Several types of optimisation designs exist. Data modelling is carried out with response surface methodology – RSM.
The construction of optimisation designs and their statistical analysis is covered with the help of real case studies.
Course Outline
Session 1: Context of Use & Objectives – Design of Optimal Designs
- Objective
- Key ideas
- Statistical concepts
- Central Composite Designs
- Box-Behnken Designs
- Optimal Designs
Session 2: Statistical Analysis of Optimisation Designs
- Response surface methodology (RSM)
- Modelling: training, validation
- Use of Model
Course Duration
The recommended course duration is 2 online sessions.
Target Audience
This course is aimed at engineers, researchers, biologists and depending on the target audience, the course is adapted. On the one hand by using examples specific to the field of application and on the other hand by presenting specific tools or applications, if applicable. This module introduces advanced concepts in DoE and corresponding data analysis methods (factorial designs and multi-way ANOVA and linear regression).
Participants must be familiar with the construction of factorial designs and analysis of variance, i.e. have followed the training courses indicated below or have an equivalent level: